Train Type Identification at S&C

Abstract EN

The presented paper concerns the development of condition monitoring system for railroad switches and crossings that utilizes vibration data.

Successful utilization of such system requires a robust and efficient train type identification.

Given the complex and unique dynamical response of any vehicle track interaction, the machine learning was chosen as a suitable tool.

For design and validation of the system, real on-site acceleration data were used.

The resulting theoretical and practical challenges are discussed.